Sentence examples for large scale bias from inspiring English sources

Exact(1)

Whether these findings may have been biased due to detection issues related to prostate cancer screening, the positive associations seen across strata of number of PSA tests and lack of evidence of heterogeneous effects would suggest no large scale bias among this particular subgroup, although we recognize the lack of significant findings in all of the strata limits any clear conclusion.

Similar(59)

The existence of more large scale biases is also supported by the findings that for decoding other stimulus dimensions, such as orientation and direction of motion [34], [20], [35], [21], [22], spatial smoothing does not diminish decoding accuracy and can even improve it.

Moreover, we observed consistent effects among both African Americans and Caucasians, indicating that large-scale bias due to underlying population structure is unlikely to have occurred.

This integrated genome annotation will reduce database variation bias in large scale gene expression studies.

This bias corresponds to a -0.17 m bias on the change in InSAR surface height, and this illustrates that a minor bias on the derived DSMs and their changes over time can generate a considerable error if the bias occurs at large scale.

Evaluation on a large scale is needed to confirm those bias corrections.

14 A relatively low number of studies met our inclusion criteria, but these strict criteria enabled us to focus on large scale high quality studies to minimise bias.

This bias corresponds to a -0.17 m bias on the change in InSAR surface height, and this illustrates that a minor bias on the derived DSMs and their changes over time can generate a considerable error if the bias occurs at large scale.

One consequence of these errors is large-scale, systematic bias in assembly and annotation.

False positive results can arise from at least the following causes: experimental noise inherent to large-scale studies, bias associated with a particular screen assay, incorrect gene models, and arguably most importantly, reagent-specific off-target effects (OTEs) (reviewed in [ 3]).

Our large scale approach confirmed the importance of genomic biases but also unveiled important translational biases that shape codon-pair context and should be primary targets for mistranslation hot spots.

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